Investigating and Optimizing the Operation of Microgrids with Intelligent Algorithms

Ahmed Kadhim Hado; Bashar S. Bashar; Musaddak Maher Abdul Zahra; Reza Alayi; Yaser Ebazadeh; Iswanto Suwarno

doi:10.18196/jrc.v3i3.14772

Authors

Ahmed Kadhim Hado Civil Engineering Department, University of Warith Al-Anbiyaa, Karbala, Iraq
Bashar S. Bashar Department of Engineering/Al-Nisour University College/Baghdad/Iraq
Musaddak Maher Abdul Zahra 3 Computer Techniques Engineering Department, Al-Mustaqbal University College, Hillah 51001, Iraq 4 Electrical Engineering Department, College of Engineering, University of Babylon, Hilla, Babil, Iraq
Reza Alayi Department of Computer Engineering, Germi Branch, Islamic Azad University, Germi, Iran http://orcid.org/0000-0003-2190-1185
Yaser Ebazadeh Department of Computer Engineering, Germi Branch, Islamic Azad University, Germi, Iran
Iswanto Suwarno Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta, Indonesia

DOI:

https://doi.org/10.18196/jrc.v3i3.14772

Keywords:

Microgrids, Short-term planning, Power systems, Optimal load distribution, Neuro-Fuzzy Network,

Abstract

Microgrids need optimization to reduce economic problems and human losses. Scattered resources in power systems and microgrids have led to many environmental, economic and human, and animal losses. The most important part of these problems is related to voltage and frequency fluctuations when possible occurrences such as extreme load changes or errors in microgrids. These problems lead to microgrid collapse. Therefore, providing optimal solutions that can solve these challenges is essential. For this purpose, the present study has tried to provide a high-performance control structure in the time of internal and external disturbances based on short-term planning. The proposed approach is the use of an evolutionary neuro-fuzzy network. Perhaps the main reason for using this approach can be due to uncertainty in the distribution and distribution of loads in microgrids and power systems. Simulation has been performed in MATLAB and Simulink environments, and the results show that the optimal load distribution has been done evolution in microgrids.

Author Biography

Reza Alayi, Department of Computer Engineering, Germi Branch, Islamic Azad University, Germi, Iran

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